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Progress in Artificial Intelligence
This book contains a selection of higher quality and reviewed papers of the 14th Portuguese Conference on Artificial Intelligence, EPIA 2009, held in Aveiro, Portugal, in October 2009. The 55 revised full papers presented were carefully reviewed and selected from a total of 163 submissions. The papers are organized in topical sections on artificial intelligence in transportation and urban mobility (AITUM), artificial life and evolutionary algorithms (ALEA), computational methods in bioinformatics and systems biology (CMBSB), computational logic with applications (COLA), emotional and affective computing (EAC), general artificial intelligence (GAI), intelligent robotics (IROBOT), knowledge discovery and business intelligence (KDBI), muli-agent systems (MASTA) social simulation and modelling (SSM), text mining and application (TEMA) as well as web and network intelligence (WNI).
Machine Learning: ECML 2005
This book constitutes the refereed proceedings of the 16th European Conference on Machine Learning, ECML 2005, jointly held with PKDD 2005 in Porto, Portugal, in October 2005. The 40 revised full papers and 32 revised short papers presented together with abstracts of 6 invited talks were carefully reviewed and selected from 335 papers submitted to ECML and 30 papers submitted to both, ECML and PKDD. The papers present a wealth of new results in the area and address all current issues in machine learning.
The Oxford Handbook of Agent-based Computational Management Science
Over the past few decades, agent-based modelling and agent-based computational technologies have spread into research on business and management. Agent-based modelling takes account of individual behavior alongside interactions within and across organizations and their competitive environment, seeking to explain complex, macro-level patterns emerging from micro-level behavior. These characteristics make an agent-based approach useful for studying a number of open issues in management, including adaptive behavior and dynamics in and across organizations, variable outcomes caused by management practices, and bridging micro-and macro-levels in organizational analysis. In The Oxford Handbook of ...
Machine Learning - EWSL-91
In this book contemporary knowledge of superconductivity is set against its historical background. First, the highlights of superconductivity research in the twentieth century are reviewed. Further contributions then describe the basic phenomena resulting from the macroscopic quantum state of superconductivity (such as zero resistivity, the Meissner-Ochsenfeld effect, and flux quantization) and review possible mechaniscs, including the classical BCS theory and the more recent alternative theories. The main categories of superconductors - elements, intermetallic phases, chalcogenides, oxides and organic compounds - are described. Common features and differences in their structure and electronic properties are pointed out. This broad overview of superconductivity is completed by a discussion of properties related to the coherence length. Newcomers to the field who seek an overall picture of research in superconductivity, and of the cross-links between its branches, will find this volume especially useful.
Anticipatory Learning Classifier Systems
Anticipatory Learning Classifier Systems describes the state of the art of anticipatory learning classifier systems-adaptive rule learning systems that autonomously build anticipatory environmental models. An anticipatory model specifies all possible action-effects in an environment with respect to given situations. It can be used to simulate anticipatory adaptive behavior. Anticipatory Learning Classifier Systems highlights how anticipations influence cognitive systems and illustrates the use of anticipations for (1) faster reactivity, (2) adaptive behavior beyond reinforcement learning, (3) attentional mechanisms, (4) simulation of other agents and (5) the implementation of a motivational ...
Data Mining and Knowledge Discovery Handbook
Knowledge Discovery demonstrates intelligent computing at its best, and is the most desirable and interesting end-product of Information Technology. To be able to discover and to extract knowledge from data is a task that many researchers and practitioners are endeavoring to accomplish. There is a lot of hidden knowledge waiting to be discovered – this is the challenge created by today’s abundance of data. Data Mining and Knowledge Discovery Handbook, Second Edition organizes the most current concepts, theories, standards, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This handbook...
Complex Data Warehousing and Knowledge Discovery for Advanced Retrieval Development: Innovative Methods and Applications
Recently, researchers have focused on challenging problems facing the development of data warehousing, knowledge discovery, and data mining applications.
ECAI 2010
LC copy bound in 2 v.: v. 1, p. 1-509; v. 2, p. [509]-1153.
Machine Learning
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